Skip to main content
SpringerLink
Log in

Study on Equal Interval Sampling Method Promoting Efficiency of Post-Processing Algorithms for Infrared Thermography Inspecting Carbon-Fiber Reinforced Plastics Composites

  • THERMAL METHODS
  • Published:
Russian Journal of Nondestructive Testing Aims and scope Submit manuscript

Abstract

The broadening use of carbon-fiber reinforced plastics (CFRP) in various industries has raised safety concerns. To control the hazard, infrared thermography inspection techniques, capable of large-area scanning, instantaneous imaging, and completely non-contact detection, has been increasingly adopted to detect flaws inside CFRP structures. And in practical engineering, post-processing algorithms are required to eliminate noise and enhance defect detectability after initial inspection course. However, rapid updates of infrared camera bring high-resolution thermograms yet. Whereas classic algorithms have encountered data explosion problem which led to low efficiency and engineering infeasibility. Therefore, to promote the efficiency of postprocessing algorithms, we propose equal interval sampling (EIS) method to sample raw thermal data. Two CFRP laminates with embedded artificial Teflon inserts of different sizes at different depths are inspected by a laser infrared thermography system. The obtained raw thermal videos made up of 500 frame thermal images with 512 × 640 pixels were converted to 3D thermographic data. We apply EIS to sample the data by setting different intervals. And the sampled data are fed to classic post-processing algorithms, thermal signal reconstruction (TSR) and principal component analysis (PCA), which have prevailed in processing thermographic data. Regarding different intervals of EIS as variables, the processing efficiency, and the defect detection performance of EIS-TSR and EIS-PCA are studied. The results demonstrate that EIS-TSR method fails to promote processing speed and maintain the performance of defect detection at the same time. In contrast, the EIS-PCA method attains a remarkable efficiency and intact defect detectability simultaneously, manifesting its adequacy in engineering practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
Fig. 9.
Fig. 10.
Fig. 11.
Fig. 12.
Fig. 13.
Fig. 14.

REFERENCES

  1. Guoyi Hou, Jianping Qiu, Kaifu Zhang, Sipeng Cao, Hui Cheng, Bin Luo, and Yi Cheng, Comparative tool wear and hole quality investigation in drilling of aerospace grade T800 CFRP using different external cooling lubricants, Int. J. Adv. Manuf. Technol., 2020, vol. 106, p. 937–951. https://doi.org/10.1007/s00170-019-04554-9

    Article  Google Scholar 

  2. Jokinen, J. and Kanerva, M., Simulation of delamination growth at CFRP-tungsten aerospace laminates using VCCT and CZM modelling techniques, Appl. Compos. Mater., 2019, vol. 26, p. 709–721. https://doi.org/10.1007/s10443-018-9746-5

    Article  CAS  Google Scholar 

  3. Meltem Altin Karataş and Hasan Gökkaya, A review on machinability of carbon fiber reinforced polymer (CFRP) and glass fiber reinforced polymer (GFRP) composite materials, Def. Technol., 2018, vol. 14, no. 4, pp. 54–62. https://doi.org/10.1016/j.dt.2018.02.001

    Article  Google Scholar 

  4. Doroudi, Y., Fernando, D., Nguyen, V.T., and Torres, J.P., Experimental study on CFRP-to-steel bonded interfaces under quasi-static cyclic loading, J. Compos. Constr., 2019, vol. 23, no. 4, p. 04019023. https://doi.org/10.1061/(ASCE)CC.1943-5614.0000945

  5. Leslie Bustamante, Jeyaprakash, N., and Che-Hua Yang, Evaluation of defect detection in aluminum, CFRP and epoxy resin plates using non-contact air-coupled ultrasonic waves, Int. J. Precis. Eng. Manuf., 2020, vol. 21, pp. 1843–1856. https://doi.org/10.1007/s12541-020-00386-w

    Article  Google Scholar 

  6. Shichun Wu, Bin Gao, Yang Yang, Yuyu Zhu, Pietro Burrascano, Stefano Laureti, Marco Ricci, and Yizhe Wang, Halogen optical referred pulse-compression thermography for defect detection of CFRP, Infrared Phys. Tech., 2019, vol. 102, p. 103006. https://doi.org/10.1016/j.infrared.2019.103006

    Article  CAS  Google Scholar 

  7. Loïc Séguin-Charbonneau, Julien Walter, Louis-Daniel Théroux, Laurent Scheed, Alexandre Beausoleil, and Benoit Masson, Automated defect detection for ultrasonic inspection of CFRP aircraft components, NDT & E Int., 2021, vol. 122, p. 102478. https://doi.org/10.1016/j.ndteint.2021.102478

    Article  CAS  Google Scholar 

  8. Koichi Mizukami, Yoshihiro Mizutani, Akira Todoroki, and Yoshiro Suzuki, Detection of in-plane and out-of-plane fiber waviness in unidirectional carbon fiber reinforced composites using eddy current testing, Compos. Part B-Eng., 2016, vol. 86, pp. 84–94. https://doi.org/10.1016/j.compositesb.2015.09.041

    Article  CAS  Google Scholar 

  9. Li, Y., Song, Y.J., and Chen, W.H., Infrared thermography for on-line examination of the CFRP impact damage, Strength Mater., 2021, vol. 53, pp. 88–96. https://doi.org/10.1007/s11223-021-00264-4

    Article  CAS  Google Scholar 

  10. Qiang Wang, Qiuping Hu, Jinxing Qiu, Cuixiang Pei, Xinyi Li, Hongbin Zhou, Ruicong Xia, and Jia Liu, Image enhancement method for laser infrared thermography defect detection in aviation composites, Opt. Eng., 2019, vol. 58, no. 10, p. 103104. https://doi.org/10.1117/1.OE.58.10.103104

    Article  Google Scholar 

  11. Munawar Sarker, Ali Hadigheh Ali, S., and Daniel Dias-da-Costa, A performance-based characterisation of CFRP composite deterioration using active infrared thermography, Compos. Struct., 2020, vol. 241, p. 112134. https://doi.org/10.1016/j.compstruct.2020.112134

    Article  Google Scholar 

  12. ASTM E2582-07, Standard Practice for Infrared Flash Thermography of Composite Panels and Repair Patches Used in Aerospace Applications, 2014.

  13. Vavilov, V.P. and Burleigh, D.D., Review of pulsed thermal NDT: Physical principles, theory and data processing, NDT & E Int., 2015, vol. 73, pp. 28–52. https://doi.org/10.1016/j.ndteint.2015.03.003

  14. Shepard, S.M., Advances in pulsed thermography, Proc. SPIE, 2001, vol. 4360, p. Thermosense XXIII. https://doi.org/10.1117/12.421032

  15. Shepard, S.M., US Patent US6516084 B2. Temporal noise reduction, compression and analysis of thermographic image data sequences, 2003.

  16. Rajic, N., Principal component thermography for flaw contrast enhancement and flaw depth characterisation in composite structures, Compos. Struct., 2002, vol. 58, no. 4, pp. 521–528. https://doi.org/10.1016/S0263-8223(02)00161-7

    Article  Google Scholar 

  17. Saeid Hedayatrasa, Gaétan Poelman, Joost Segers, Wim Van Paepegem and Mathias Kersemans, On the application of an optimized frequency-phase modulated waveform for enhanced infrared thermal wave radar imaging of composites, Opt. Laser Eng., 2021, col. 138, p. 106411. https://doi.org/10.1016/j.optlaseng.2020.106411

  18. Wen, C.-M., Sfarra, S., Gargiulo, G., and Yao, Y., Thermographic data analysis for defect detection by imposing spatial connectivity and sparsity constraints in principal component thermography, IEEE Ind. Inf., 2021, vol. 17, no. 6, pp. 3901–3909. https://doi.org/10.1109/TII.2020.3010273

    Article  Google Scholar 

  19. Walter Nsengiyumva, Shuncong Zhong, Jiewen Lin, Qiukun Zhang, Jianfeng Zhong, and Yuexin Huang, Advances, limitations and prospects of nondestructive testing and evaluation of thick composites and sandwich structures: A state-of-the-art review, Compos. Struct., 2021, vol. 256, p. 112951. https://doi.org/10.1016/j.compstruct.2020.112951

    Article  Google Scholar 

  20. Vandenrijt, J.F., Lievre, N., and Georges, M.P., Improvement of defect detection in shearography by using Principal Component Analysis, Conf. Interferometry: Tech. Anal. (2014), p. 92030L.1.

Download references

Funding

This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.

Author information

Authors and Affiliations

  1. Equipment Management and Unmanned Aerial Vehicle Engineering School, Air Force Engineering University, 710051, Xi’an, Shaanxi Province, China

    Qiang Wang, Ruicong Xia & Qiuhan Liu

Authors
  1. Qiang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ruicong Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qiuhan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Qiang Wang, Ruicong Xia or Qiuhan Liu.

Ethics declarations

The authors of this work declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Q., Xia, R. & Liu, Q. Study on Equal Interval Sampling Method Promoting Efficiency of Post-Processing Algorithms for Infrared Thermography Inspecting Carbon-Fiber Reinforced Plastics Composites. Russ J Nondestruct Test 59, 804–814 (2023). https://doi.org/10.1134/S106183092360020X

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S106183092360020X

Keywords:

Search

Navigation